"1. Sales & Revenue Metrics
Total Units Sold – Tracks overall headset sales volume.
Revenue Growth (%) – Measures whether revenue is increasing from headset sales over time.
Sales by Channel – Identifies how sales are distributed across Google Store, third-party retailers (Amazon, Best Buy), and carrier partnerships.
Sales by Region – Helps understand geographic demand and refine regional marketing efforts.
Attach Rate – Measures how often the headset is purc"
fuzzyicecream14 - "1. Sales & Revenue Metrics
Total Units Sold – Tracks overall headset sales volume.
Revenue Growth (%) – Measures whether revenue is increasing from headset sales over time.
Sales by Channel – Identifies how sales are distributed across Google Store, third-party retailers (Amazon, Best Buy), and carrier partnerships.
Sales by Region – Helps understand geographic demand and refine regional marketing efforts.
Attach Rate – Measures how often the headset is purc"See full answer
"Clarify
10X -> usage or revenue
Approach
What is Msft Copilot & key capabilities
Understand the space in which Copilot operates :
Target segments & use-cases serve
Competitors (alternatives)
Leverage microsoft has :
Understand the stack (infra -> application layer) -> leverage
Understand Microsoft ecosystem & leverage we have
Define : 10X growth strategy (for whom -> & what? -> distribution (acquire & retain))
MSft Copilot & key capabilities
Cons"
Neeraj K. - "Clarify
10X -> usage or revenue
Approach
What is Msft Copilot & key capabilities
Understand the space in which Copilot operates :
Target segments & use-cases serve
Competitors (alternatives)
Leverage microsoft has :
Understand the stack (infra -> application layer) -> leverage
Understand Microsoft ecosystem & leverage we have
Define : 10X growth strategy (for whom -> & what? -> distribution (acquire & retain))
MSft Copilot & key capabilities
Cons"See full answer
"Restaurant Types
High-end
Fast-food
Regular
User Types
Restaurants – seeking operational efficiency and increased revenue.
Customers – categorized by group size and dining intent:
2–4 Friends/Family – casual dining.
Solo Diners – convenience and quick service.
Groups > 4 – shared orders and split bills.
Goal
Design a tablet solution to achieve product-market fit by addressing key pain points and driving high ad"
Brandy L. - "Restaurant Types
High-end
Fast-food
Regular
User Types
Restaurants – seeking operational efficiency and increased revenue.
Customers – categorized by group size and dining intent:
2–4 Friends/Family – casual dining.
Solo Diners – convenience and quick service.
Groups > 4 – shared orders and split bills.
Goal
Design a tablet solution to achieve product-market fit by addressing key pain points and driving high ad"See full answer
"1) Clarifications
Is this a Google initiative? Yes
Timeline for development? MVP within 3 months.
Hotel type? Focus on urban and mid-sized hotels
Items to offer? Include ready-to-eat meals/snacks (e.g., microwaveable food, healthy snacks, beverages).
Geographic scope? Launch in the US only.
2) Google Mission / Why
"Organize the world’s information and make it universally accessible and useful."
Google aims to enhance the guest experienc"
Carlos S. - "1) Clarifications
Is this a Google initiative? Yes
Timeline for development? MVP within 3 months.
Hotel type? Focus on urban and mid-sized hotels
Items to offer? Include ready-to-eat meals/snacks (e.g., microwaveable food, healthy snacks, beverages).
Geographic scope? Launch in the US only.
2) Google Mission / Why
"Organize the world’s information and make it universally accessible and useful."
Google aims to enhance the guest experienc"See full answer
Product Manager
Product Design
🧠 Want an expert answer to a question? Saving questions lets us know what content to make next.
"Clarifications:
Which aspect of birthday are we thinking about designing a product for? Birthday reminder, birthday planning, event management or birthday wishing?-
People are generally reminded of their birthdays by their friends/family, social media, their own self awareness, so its not a critical problem to solve
Social apps like FB have birthday wishing features for the larger audience & for wishing friends/family, people would generally call or wish in person
Manag"
Debajyoti B. - "Clarifications:
Which aspect of birthday are we thinking about designing a product for? Birthday reminder, birthday planning, event management or birthday wishing?-
People are generally reminded of their birthdays by their friends/family, social media, their own self awareness, so its not a critical problem to solve
Social apps like FB have birthday wishing features for the larger audience & for wishing friends/family, people would generally call or wish in person
Manag"See full answer
"First, I’d want to clarify what’s driving the lack of adoption.
I’d ask:What does “unclear roadmap” mean? Is this an internal issue where we’re not addressing customer pain points, or is it a matter of customers not understanding how to use the product?
Is this feedback coming from all enterprise customers across verticals, or is it isolated to a specific group?
How long has this been going on? Has it been over a quarter?
Assuming this is a widespread issue impacting all customers"
Noe L. - "First, I’d want to clarify what’s driving the lack of adoption.
I’d ask:What does “unclear roadmap” mean? Is this an internal issue where we’re not addressing customer pain points, or is it a matter of customers not understanding how to use the product?
Is this feedback coming from all enterprise customers across verticals, or is it isolated to a specific group?
How long has this been going on? Has it been over a quarter?
Assuming this is a widespread issue impacting all customers"See full answer
"Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"
Joshua R. - "Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"See full answer
"Context / clarifying questions:
Should I assume this is part of Google company?
Let’s assume yes
Let’s assume we’re building this for Waymo, Google parent company
Self-driving cars industry today
It’s evolving a lot. I do not have much information on the industry but I know Waymo self driving cars are progressing and there are self-driving taxis already running.
Why are we building this and why are we building this now
Mainly to understand if this makes sense to"
Sofiya H. - "Context / clarifying questions:
Should I assume this is part of Google company?
Let’s assume yes
Let’s assume we’re building this for Waymo, Google parent company
Self-driving cars industry today
It’s evolving a lot. I do not have much information on the industry but I know Waymo self driving cars are progressing and there are self-driving taxis already running.
Why are we building this and why are we building this now
Mainly to understand if this makes sense to"See full answer
"The question is bit vague (I guess deliberately) so I believe firstly we shall ask questions and resolve ambiguity. Some initial questions could be :
1) Is this one time activity or something that should be done on continuous basis. If continuous basis then at what frequency.
2) How much staleness is acceptable in SYSTEM Y data
3) Are there any limitation in SYSTEM Y and is it fair to assume that we would need some kind of transformation to bring data into SYSTEM Y schema.
4) What kind of vol"
Kshitij A. - "The question is bit vague (I guess deliberately) so I believe firstly we shall ask questions and resolve ambiguity. Some initial questions could be :
1) Is this one time activity or something that should be done on continuous basis. If continuous basis then at what frequency.
2) How much staleness is acceptable in SYSTEM Y data
3) Are there any limitation in SYSTEM Y and is it fair to assume that we would need some kind of transformation to bring data into SYSTEM Y schema.
4) What kind of vol"See full answer
"def encode(root):
if not root:
return []
def dfs(node):
if not node:
return
res.append(node.val)
res.append(len(node,children))
for child_node in node.children:
dfs(child_node)
res = []
dfs(root)
return res
def decode(arr):
if not arr:
return None
n = len(arr)
i = 0
def dfs(val, children_count):
if children_count == 0:
return Node(val)
cur_node = Node(val)
cur_node.children = []
for j in range(children_count):
nonlocal i
i += 2
cur_node.children.append(dfs(arr[i], arr[i"
Ying T. - "def encode(root):
if not root:
return []
def dfs(node):
if not node:
return
res.append(node.val)
res.append(len(node,children))
for child_node in node.children:
dfs(child_node)
res = []
dfs(root)
return res
def decode(arr):
if not arr:
return None
n = len(arr)
i = 0
def dfs(val, children_count):
if children_count == 0:
return Node(val)
cur_node = Node(val)
cur_node.children = []
for j in range(children_count):
nonlocal i
i += 2
cur_node.children.append(dfs(arr[i], arr[i"See full answer
"To build a product using Generative AI (Gen AI), the process would involve multiple steps, from conceptualization to deployment. Here's a structured approach :
1. Identify the Problem or Opportunity
Start with the need or opportunity: What problem do you want to solve? Is it to automate tasks, generate content, enhance creativity, or improve user experience?
Example products:A content creation tool that generates blog posts or articles.
A personalized customer support chatbot"
Maulik S. - "To build a product using Generative AI (Gen AI), the process would involve multiple steps, from conceptualization to deployment. Here's a structured approach :
1. Identify the Problem or Opportunity
Start with the need or opportunity: What problem do you want to solve? Is it to automate tasks, generate content, enhance creativity, or improve user experience?
Example products:A content creation tool that generates blog posts or articles.
A personalized customer support chatbot"See full answer
"Answering only estimation portion for practice (for some reason after submitting the formatting is unorganized)
clarification and assumptions
can I assume this grocery store location is called Greens
can I assume that self-checkout means that customers checks out without assistance?
can I assume that cashier checkout means that cashier assists customers with checkout?
can I assume that ratio means how man self-checkouts should be place at this grocery store compare"
Ama M. - "Answering only estimation portion for practice (for some reason after submitting the formatting is unorganized)
clarification and assumptions
can I assume this grocery store location is called Greens
can I assume that self-checkout means that customers checks out without assistance?
can I assume that cashier checkout means that cashier assists customers with checkout?
can I assume that ratio means how man self-checkouts should be place at this grocery store compare"See full answer
"I believe these are the traits of a great PM. I see PM to be somone who is a great manager of customer problems and for that he/she has to be:
Be an expert at the one domain and know the customer of the product in that domain and curate experiences for them better than the competition.
Be persuasive - Get things done by convincing rather than commanding.
Learn how great products are by being an engineer.
Be a fearless leader by championing teams ideas all the way to the management la"
Siddharth P. - "I believe these are the traits of a great PM. I see PM to be somone who is a great manager of customer problems and for that he/she has to be:
Be an expert at the one domain and know the customer of the product in that domain and curate experiences for them better than the competition.
Be persuasive - Get things done by convincing rather than commanding.
Learn how great products are by being an engineer.
Be a fearless leader by championing teams ideas all the way to the management la"See full answer
"Clarifying question: normally when we say design for , we mean the same product with features for the user segment. Here, is it okay to assume the meaning to be design a product from Netflix for dogs?
Assumption: yes.
Reason for assumption: an OTT app in its current form with movies and web series is not very suitable to dogs.
We will start by analysing who the stakeholders are in the users.
Dogs
Pet owners
Shelter workers.
We will now explore some of t"
Upasana S. - "Clarifying question: normally when we say design for , we mean the same product with features for the user segment. Here, is it okay to assume the meaning to be design a product from Netflix for dogs?
Assumption: yes.
Reason for assumption: an OTT app in its current form with movies and web series is not very suitable to dogs.
We will start by analysing who the stakeholders are in the users.
Dogs
Pet owners
Shelter workers.
We will now explore some of t"See full answer